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首页> 外文期刊>Journal of manufacturing science and engineering: Transactions of the ASME >An Alternate Approach to SHPB Tests to Compute Johnson-Cook Material Model Constants for 97 WHA at High Strain Rates and Elevated Temperatures Using Machining Tests
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An Alternate Approach to SHPB Tests to Compute Johnson-Cook Material Model Constants for 97 WHA at High Strain Rates and Elevated Temperatures Using Machining Tests

机译:SHPB测试的替代方法,以在高应变率高的高应变速率下计算97 WHA的Johnson-Cook材料模型常数,并使用加工测试升高温度

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摘要

With advances in computational techniques, numerical methods such as finite element method (FEM) are gaining much of the popularity for analysis as these substitute the expensive trial and error experimental techniques to a great extent. Consequently, selection of suitable material models and determination of precise material model constants are one of the prime concerns in FEM. This paper presents a methodology to determine the Johnson-Cook constitutive equation constants (JC constants) of 97 W Tungsten heavy alloys (WHAs) under high strain rate conditions using machining tests in conjunction with Oxley's predictive model and particle swarm optimization (PSO) algorithm. Currently, availability of the high strain rate data for 97 WHA are limited and consequently, JC constants for the same are not readily available. The overall methodology includes determination of three sets of JC constants, namely, M1 and M2 from the Split-Hopkinson pressure bar (SHPB) test data available in literature by using conventional optimization technique and artificial bee colony (ABC) algorithm, respectively. However, M3 is determined from machining tests using inverse identification method. To validate the identified JC constants, machining outputs (cutting forces, temperature, and shear strain) are predicted using finite element (FE) model by considering M1, M2, and M3 as input under different cutting conditions and then validated with corresponding experimental values. The predicted outputs obtained using JC constants M3 closely matched with that of the experimental ones with error percentage well within 10%.
机译:随着计算技术的进步,有限元法(FEM)等数值方法在很大程度上取代了昂贵的试错实验技术,因此在分析中越来越受欢迎。因此,选择合适的材料模型和确定精确的材料模型常数是有限元法的主要关注点之一。本文提出了一种在高应变速率条件下,利用机械加工试验,结合Oxley预测模型和粒子群优化(PSO)算法确定97 W钨重合金(WHA)约翰逊-库克本构方程常数(JC常数)的方法。目前,97 WHA的高应变率数据的可用性是有限的,因此,同样的JC常数不容易获得。总体方法包括分别使用传统优化技术和人工蜂群(ABC)算法,从文献中提供的分离式霍普金森压杆(SHPB)测试数据中确定三组JC常数,即M1和M2。然而,M3是通过使用反向识别方法的加工试验确定的。为了验证确定的JC常数,使用有限元(FE)模型预测加工输出(切削力、温度和剪切应变),将M1、M2和M3作为不同切削条件下的输入,然后用相应的实验值进行验证。用JC常数M3得到的预测结果与实验结果吻合较好,误差在10%以内。

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